TY - JOUR
T1 - Modeling hydration kinetics of sustainable cementitious binders using an advanced nucleation and growth approach
AU - Han, Taihao
AU - Huang, Jie
AU - Sant, Gaurav
AU - Neithalath, Narayanan
AU - Goel, Ashutosh
AU - Kumar, Aditya
N1 - Publisher Copyright:
© 2023
PY - 2023/11/10
Y1 - 2023/11/10
N2 - Supplementary cementitious materials (SCMs) are utilized to partially substitute Portland cement (PC) in binders, reducing carbon-footprint and maintaining excellent performance. Nonetheless, predicting the hydration kinetics of [PC + SCM] binders is challenging for current analytical models due to the extensive diversity of chemical compositions and molecular structures present in both SCMs and PC. This study develops an advanced phase boundary nucleation and growth (pBNG) model to yield a priori predictions of hydration kinetics—i.e., time-resolved exothermic heat release profiles—of [PC + SCM] binders. The advanced pBNG model integrates artificial intelligence as an add-on, enabling it to accurately simulate hydration kinetics for [PC + SCM] binders. This study utilizes a database that includes calorimetry profiles of 710 [PC + SCM] binders, encompassing a diverse range of commonly-used SCMs as well as both commercial and synthetic PCs. The results show that the advanced pBNG model predicts the heat evolution profiles of [PC + SCM] in a high-fidelity manner.
AB - Supplementary cementitious materials (SCMs) are utilized to partially substitute Portland cement (PC) in binders, reducing carbon-footprint and maintaining excellent performance. Nonetheless, predicting the hydration kinetics of [PC + SCM] binders is challenging for current analytical models due to the extensive diversity of chemical compositions and molecular structures present in both SCMs and PC. This study develops an advanced phase boundary nucleation and growth (pBNG) model to yield a priori predictions of hydration kinetics—i.e., time-resolved exothermic heat release profiles—of [PC + SCM] binders. The advanced pBNG model integrates artificial intelligence as an add-on, enabling it to accurately simulate hydration kinetics for [PC + SCM] binders. This study utilizes a database that includes calorimetry profiles of 710 [PC + SCM] binders, encompassing a diverse range of commonly-used SCMs as well as both commercial and synthetic PCs. The results show that the advanced pBNG model predicts the heat evolution profiles of [PC + SCM] in a high-fidelity manner.
KW - Growth rate
KW - Hydration kinetics
KW - Nucleation and growth
KW - Sustainable cementitious binders
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U2 - 10.1016/j.conbuildmat.2023.133327
DO - 10.1016/j.conbuildmat.2023.133327
M3 - Article
AN - SCOPUS:85170636861
SN - 0950-0618
VL - 404
JO - Construction and Building Materials
JF - Construction and Building Materials
M1 - 133327
ER -